Adaptive event‐triggered neural control for nonlinear uncertain system with input constraint

In this article, the issue of developing an adaptive event‐triggered neural control for nonlinear uncertain system with input delay is investigated. The radial basis function neural networks (RBFNNs) are adopted to approximate the uncertain terms, where the time‐varying approximation errors are considered into the approximation system. However, the RBFNNs' weight vector is extended, which may cause the computing burdens. To save network resource, the computing burden caused by the weight vector is handled with the developed adaptive control strategy. Furthermore, in order to compensate the effect of input delay, an auxiliary system is introduced into codesign. With the help of adaptive backstepping technique, an adaptive event‐triggered control approach is established. Under the proposed control approach, the effect of input delay can be compensated effectively while the considered system suffered network resource constraint, and all signals in the close‐loop system can be guarantee bounded. Finally, two simulation examples are given to verify the proposed control method's effectiveness.     

输入受限的非线性系统自适应模糊backstepping控制

针对一类输入受限的非线性系统,提出了一种自适应模糊backsteppig控制器的设计方法.在控制器的设计过程当中,采用模糊系统对不确定非线性函数在线逼近;利用双曲正切函数和Nussbaum函数对系统输入饱和函数进行处理;将动态面法与backstepping法相结合解决"计算膨胀"的问题.通过Lyapunov理论分析证明了所设计的控制器能够使闭环系统所有信号半全局一致有界(SGUUB).最后应用于高超声速飞行器的攻角跟踪控制中,仿真结果表明该方法的有效性.     

Adaptive neural network tracking control for uncertain nonlinear systems with input delay and saturation

In this article, the adaptive tracking control problem is considered for a class of uncertain nonlinear systems with input delay and saturation. To compensate for the effect of the input delay and saturation, a compensation system is designed. Radial basis function neural networks are directly utilized to approximate the unknown nonlinear functions. With the aid of the backstepping method, novel adaptive neural network tracking controllers are developed, which can guarantee all the signals in the closed‐loop system are semiglobally uniformly ultimately bounded, and the system output can track the desired signal with a small tracking error. In the end, a simulation example is given to illustrate the effectiveness of the proposed methods.     

Robust control for a class of uncertain nonlinear systems with input quantization

In this paper, we propose a robust tracking control scheme for a class of uncertain strict‐feedback nonlinear systems. In these systems, the control signal is quantized by a class of sector‐bounded quantizers including the well‐known hysteresis quantizer and logarithmic quantizer. Compared with the existing results in input‐quantized control, the proposed scheme can control systems with non‐global Lipschitz nonlinearities and unmatched uncertainties caused by model uncertainties and external disturbances. It is shown that the designed robust controller ensures global boundedness of all the signals in the closed‐loop system and enables the tracking error to converge toward a residual, which can be made arbitrarily small. Copyright © 2015 John Wiley & Sons, Ltd.     

Sliding mode control design for uncertain time‐delay systems subjected to a class of nonlinear inputs

A sliding mode controller is developed for uncertain time‐delay systems with a class of nonlinear inputs. Two main results are derived in this paper. The first result is the presentation of a new delay‐dependent stability condition of uncertain time‐delay systems. In a comparison example, this stability condition is shown to be less conservative than the ones reported recently. The second result is to present a new sliding mode control for uncertain time‐delay systems subjected to a class of nonlinear inputs. The stability of time‐delay systems with unmatching condition in the sliding mode is also discussed. Two illustrative examples are included to demonstrate the superiority of the obtained results. Copyright © 2003 John Wiley & Sons, Ltd.     

Adaptive fuzzy switched control design for uncertain nonholonomic systems with input nonsmooth constraint

In this paper, a fuzzy adaptive switched control approach is proposed for a class of uncertain nonholonomic chained systems with input nonsmooth constraint. In the control design, an auxiliary dynamic system is designed to address the input nonsmooth constraint, and an adaptive switched control strategy is constructed to overcome the uncontrollability problem associated with x₀(t₀) = 0. By using fuzzy logic systems to tackle unknown nonlinear functions, a fuzzy adaptive control approach is explored based on the adaptive backstepping technique. By constructing the combination approximation technique and using Young's inequality scaling technique, the number of the online learning parameters is reduced to n and the ‘explosion of complexity’ problem is avoid. It is proved that the proposed method can guarantee that all variables of the closed-loop system converge to a small neighbourhood of zero. Two simulation examples are provided to illustrate the effectiveness of the proposed control approach.     

一类高阶非线性不确定系统自适应稳定控制

研究了一类高阶非线性不确定性系统的自适应稳定控制设计问题.因该系统的非线性程度高,其控制系数不等同、符号已知、但数值未知,故在此之前其稳定控制设计问题没有得到解决.本文应用自适应技术,结合设计参数的适当选取,从而得到了设计该类非线性系统状态反馈稳定控制器的新方法,并基于反推技术,给出了稳定控制器的设计步骤.所设计的状态反馈控制器使得闭环系统的状态全局渐近收敛于零,其余闭环信号一致有界.最后通过一个仿真例子说明了控制设计方法的有效性.     

Adaptive quantised fault-tolerant tracking control of uncertain nonlinear systems with unknown control direction and the prescribed accuracy

In this paper, the problem of adaptive fault-tolerant tracking control for a class of uncertain nonlinear systems in the presence of input quantisation and unknown control direction is considered. By choosing a class of particular Nussbaum functions, an adaptive fault-tolerant control scheme is designed to compensate actuator faults and input quantisation while the control direction is unknown. Compared with the existing results, the proposed controller can directly compensate for the nonlinear term caused by actuator faults and the nonlinear decomposition on the quantiser without estimating its bound. Furthermore, via Barhalant's Lemma, it is proven that all the signals of the closed-loop system are globally uniformly bounded and the tracking error converges into a prescribed accuracy in prior. Finally, an illustrative example is used for verifying effectiveness of the proposed approach.     

Adaptive neural control for a class of uncertain nonlinear systems with unknown time delay

A neural network (NN)‐based robust adaptive control design scheme is developed for a class of nonlinear systems represented by input–output models with an unknown nonlinear function and unknown time delay. By approximating on‐line the unknown nonlinear functions with a three‐layer feedforward NN, the proposed approach does not require the unknown parameters to satisfy the linear dependence condition. The control law is delay independent and possible controller singularity problem is avoided. It is proved that with the proposed neural control law, all the signals in the closed‐loop system are semiglobally bounded in the presence of unknown time delay and unknown nonlinearity. A simulation example is presented to demonstrate the method. Copyright © 2008 John Wiley & Sons, Ltd.     

Observer‐based Adaptive fuzzy control of time‐delay uncertain nonlinear systems

An observer‐based adaptive fuzzy model following controller is proposed for a class of MIMO nonlinear uncertain systems to cope with time‐delay, uncertainty in plant structure and disturbances. Based on universal approximation theorem the unknown nonlinear functions are approximated by fuzzy systems, where the premise and the consequent parts of the fuzzy rules are tuned with adaptive schemes. To have more robustness, and at the same time to alleviate chattering, an adaptive discontinuous structure is suggested. Moreover, the availability of the states measurement is not required and an adaptive observer is used to estimate the states. Asymptoic stability of the overall system is ensured using suitable a Lyapunov‐Krasovskii functional candidate. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Adaptive quantized tracking control for uncertain switched nonstrict‐feedback nonlinear systems with discrete and distributed time‐varying delays

This paper is concerned with an adaptive tracking problem for a more general class of switched nonstrict‐feedback nonlinear time‐delay systems in the presence of quantized input. The system structure in a nonstrict‐feedback form, the discrete and distributed time‐varying delays, the sector‐bounded quantized input, and arbitrary switching behavior are involved in the considered systems. In particular, to overcome the difficulties from the distributed time‐varying delays and the sector‐bounded quantized input, the mean‐value theorem for integrals and some special techniques are exploited respectively. Moreover, by combining the Lyapunov‐Razumikhin method, dynamic surface control technique, fuzzy logic systems approximation, and variable separation technique, a quadratic common Lyapunov function is easily built for all subsystems and a common adaptive quantized control scheme containing only 1 adaptive parameter is proposed. It is shown that the tracking error converges to an adjustable neighborhood of the origin whereas all signals of the closed‐loop systems are semiglobally uniformly ultimately bounded. Finally, 2 simulation examples are provided to verify the feasibility and effectiveness of the proposed design methodology.     

非线性主动悬架系统自适应最优控制

针对非线性主动悬架系统多性能指标综合优化问题,提出一类自适应最优控制方法.首先,通过引入一阶低通滤波操作,利用系统输入输出构建结构简单且调节参数少的一类未知非线性动态估计器,在线估计系统未知非线性动态;其次,构建包含乘驾舒适度、悬架行程空间及输入能耗的性能指标函数,采用单层神经网络对最优性能指标函数进行在线逼近,并得到新的哈密尔顿函数;为实现在线求解,构建一类新的基于参数估计误差信息的自适应律,在线更新神经网络权值并计算最优控制律;最后,理论分析闭环系统稳定性和收敛性,并通过专业软件Carsim与Matlab/Simulink搭建的联合仿真平台给出的对比仿真结果,验证所提出方法可有效解决主动悬架系统多目标性能优化控制问题,提升主动悬架系统综合性能.     

非对称饱和扇形输入非线性系统的自适应模糊控制

针对一类具有未知不确定性,且状态不可测的非线性系统,考虑了输入端的饱和非对称扇区非线性特性影响,提出了系统模型未知情形下基于自适应模糊观测器的跟踪控制方案,采用Lyapunov-Krasovskii函数给出了滑模控制器参数和模糊逻辑的自适应调整律.所提方法不仅可保证闭环跟踪系统的稳定性,还削弱了传统方法对模型结构的依赖...     

Compensation of time‐varying input delay for discrete‐time nonlinear systems

We consider general discrete‐time nonlinear systems (of arbitrary nonlinear growth) with time‐varying input delays and design an explicit predictor feedback controller to compensate the input delay. Such results have been achieved in continuous time, but only under the restriction that the delay rate is bounded by unity, which ensures that the input signal flow does not get reversed, namely, that old inputs are not felt multiple times by the plant (because on such subsequent occasions, the control input acts as a disturbance). For discrete‐time systems, an analogous restriction would be that the input delay is non‐increasing. In this work, we do not impose such a restriction. We provide a design and a global stability analysis that allow the input delay to be arbitrary (containing intervals of increase, decrease, or stagnation) over an arbitrarily long finite period of time. Unlike in the continuous‐time case, the predictor feedback law in the discrete‐time case is explicit. We specialize the result to linear time‐invariant systems and provide an explicit estimate of the exponential decay rate. Carefully constructed examples are provided to illustrate the design and analytical challenges. Copyright © 2015 John Wiley & Sons, Ltd.     

Adaptive tracking control for random nonlinear system

In this note, we consider a class of strict‐feedback random nonlinear system with unknown parameters,which is different from nonlinear systems described by Itó stochastic differential equations. The skills to deal with the effect of Wiener process for stochastic nonlinear systems are not suitable for random nonlinear system. We employ separation technique to design an adaptive backstepping controller such that the output can practically track a given signal and other signals are bounded in probability. A simulation example is presented to demonstrate reasonability and efficiency of the proposed method. Copyright © 2017 John Wiley & Sons, Ltd.     

一类非线性不确定系统的自适应鲁棒控制

将一类结构和参数均未知且存在外界干扰的非线性系统,等价为具有线性结构的时变系统,在此基础上设计了自适应鲁棒控制器,包括自适应模型补偿、反馈稳定控制和鲁棒反馈控制3部分,实现闭环控制系统信号有界且跟踪误差在期望的精度范围内.理论分析和仿真结果均验证了算法的有效性.     

Adaptive dynamic surface control for uncertain nonaffine nonlinear systems

This paper focuses on the problem of adaptive control for uncertain nonaffine nonlinear systems. The original nonaffine systems are transformed into the augmented affine systems via adding an auxiliary integrator, which makes the explicit control design possible. By introducing a modified sliding mode filter in each step, a novel adaptive dynamic surface controller is proposed, where the ‘explosion of complexity’ problem inherent in the backstepping design is avoided. It is proven rigorously that for any initial control condition, the proposed adaptive scheme is able to ensure the semiglobal uniformly ultimately boundedness of all signals in the closed loop. An illustrative example is carried out to verify the effectiveness of the proposed approach. Copyright © 2016 John Wiley & Sons, Ltd.     

不确定串联非线性系统H∞鲁棒自适应控制

针对一类含有未知参数和干扰的非最小相位串联非线性系统,结合H∞控制和自适应控制方法并利用李雅普诺夫函数递推设计方法设计了状态反馈H∞自适应控制器,避免了求解Hamilton-Jacobi-Isaacs不等式设计控制器的困难.该控制器不仅保证闭环系统ISS(input-to-state)稳定,而且使得系统对于所有允许的参数不确定从干扰输入到可控输出的 L 2增益不大于给定的值.最后,给出了一个仿真例子,仿真结果充分表明了所设计的控制器的可行性和有效性.     

输入时滞非线性系统的新型动态面Funnel控制

本文针对一类带有输入时滞的不确定非线性系统, 提出了新型动态面Funnel控制方案. 首先设计补偿动态 变量将输入时滞系统转换成无时滞的系统, 仅需在递归控制的最后一步补偿, 从而优化了控制器设计过程. 其次, 构造Funnel函数, 使系统的瞬态和稳态跟踪误差被限制在给定边界内. 最后, 提出新型非线性动态面控制方法, 不仅 避免了自适应反推控制中的“微分爆炸”问题, 而且消除了边界层误差, 使得系统的跟踪误差最终渐近收敛到零. 理 论分析表明该闭环系统的所有信号一致最终有界, 仿真结果验证了该控制方案的有效性.     

Two‐stage stability control for strict‐feedback systems with input delays and input nonlinear uncertainties

In this paper, a two‐stage control procedure is proposed for stabilization of a class of strict‐feedback systems with unknown constant time delays and nonlinear uncertainties in the input. A nominal controller is first designed to compensate input time delays without considering input nonlinear uncertainties. Extended from backstepping algorithm, input delay compensation is realized by means of predicted states that are computed through integration of cascaded system dynamics, making the nominal closed‐loop system asymptotically stable. Based on the nominal controller presented for the input delay system, a multi‐timescale system is subsequently developed to estimate the unknown input nonlinearity and make the estimate approach the nominal control input as fast as possible. It is proved that the proposed control scheme can make states of the strict‐feedback systems converge to zero and all the signals of the closed‐loop systems are guaranteed to be bounded in the presence of input time delays and nonlinear uncertainties. Simulation verification is carried out to illuminate the effectiveness of the proposed control approach.